



import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


_lowercase    	=		["small", "medium", "large"]

_lowercase    	=		"lm_head.decoder.weight"
_lowercase    	=		"lm_head.weight"



def 		lowerCAmelCase__     (       UpperCamelCase_					:							str			,							UpperCamelCase_					:							str						)->	Tuple:
    A__					=       torch.load(a_						)
    A__					=       d.pop(a_						)
    os.makedirs(a_			,							exist_ok=a_						)
    torch.save(a_			,							os.path.join(a_			,							a_						)						)


if __name__ == "__main__":
   _lowercase    	=		argparse.ArgumentParser()
   parser.add_argument("--dialogpt_path", default=".", type=str)
   _lowercase    	=		parser.parse_args()
   for MODEL in DIALOGPT_MODELS:
      _lowercase    	=		os.path.join(args.dialogpt_path, F"{MODEL}_ft.pkl")
      _lowercase    	=		F"./DialoGPT-{MODEL}"
      convert_dialogpt_checkpoint(
          checkpoint_path,
          pytorch_dump_folder_path,
      )






'''simple docstring'''


import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate





@dataclass(frozen=__magic_name__			)
class  __lowercase    (	__magic_name__			):
   _a    						=   field(default="""audio-classification"""							,				metadata={"""include_in_asdict_even_if_is_default""": True}			)
   _a    						=   Features({"""audio""": Audio()}			)
   _a    						=   Features({"""labels""": ClassLabel}			)
   _a    						=   "audio"
   _a    						=   "labels"







   def 		UpperCamelCase__      (						self   ,				UpperCamelCase   )					->     Dict:
     if self.label_column not in features:
       raise ValueError(f"Column {self.label_column} is not present in features."   )
     if not isinstance(features[self.label_column]   ,				UpperCamelCase   ):
       raise ValueError(f"Column {self.label_column} is not a ClassLabel."   )
     __a								=       copy.deepcopy(self   )
     __a								=       self.label_schema.copy()
     __a								=       features[self.label_column]
     __a								=       label_schema
     return task_template







   @property
   def 		UpperCamelCase__      (						self   )					->     Dict[str, str]:
     return {
         self.audio_column: "audio",
         self.label_column: "labels",
     }



